A manager opens ChatGPT 10 minutes before a difficult conversation with a direct report. Getting actionable advice requires context, so they type out the relevant details. They enter performance history, workplace tendencies under pressure and behavioral patterns that need to change. They include a real name and specific details never meant to leave the building. After a brief pause, they press Enter.
This scene unfolds daily across organizations that prioritize data privacy. Our recent AI and People Leadership Study [add live link before publishing] found that 68% of business leaders worry about sensitive employee information entering public AI tools. That fear is grounded in truth, as 44% of managers have been sharing that same type of information to get their jobs done. Leaders face a clear gap between policy and daily practice, largely because teams lack a safe, reliable alternative to turn to for guidance.
When managers lack secure resources for delicate conversations, data safety gets traded for immediate support. Protecting employee privacy requires equipping leaders with dedicated behavioral intelligence grounded in validated science, housed entirely within a private company network where sensitive data stays secure.
Why do managers put employee data into public AI tools?
Managers navigate a direct
